Applying Machine Learning Technology to Perform Automatic Provisioning of the Optical Transport Network

Abstract

AbstractThe Optical Transport Network (OTN) is considered valuable assets to any telecom operator. One of the most crucial difficulties to the owners of the OTN is how they can supervise all of these assets in the Optical Transport Network (OTN) smartly and efficiently. Controlling the operational tasks of the OTN intelligently will overcome the wrongs behavior of the human interventions while they are provisioning the optical network and will enhance the performance of the communication networks to the end customers. One of the most encouraging technologies which can assist in the administrating the assets of the OTN is the Artificial Inelegance (AI), that can be employed in the provisioning of the optical network to perform several of the everyday tasks in the network instead of using human interventions. In this paper, for the first time, we present the machine learning (ML) as a branch of the AI technology to handle and perform the routine tasks in the OTN of Egypt in smart and automated techniques. The expected outcomes from practicing ML in managing OTN show that the time of the fault localization will be reduced from average 40 min to about 10 min and consequently this will decrease main time of repair (MTTR) by about 30 min, the number of the customer’s tickets will be lowered by about 25%, and the number of network faults will be decreased by about 75% as a result of performing the preventive maintenance tasks of the network in an automated technique, and the reply time to the clients is expected to be reduced from average 50 min to about 5 min only. These expected results prove that in the next future the artificial Inelegance with its branches will perform a significant function in managing and supervising the optical core network around the world and possibly all the communication networks will be managed by the same intelligent umbrella, this will make a significant role in optimizing the resources of the optical core networks by using intelligent and centralized platform to perform the needed tasks in the network without any human interventions, which will reduce the operational cost and will maximize the ROI from the OTN.KeywordsOptical Transport Network (OTN)Artificial Inelegance (AI)Machine learning (ML)Intelligent centralized platformHuman interventionEveryday tasks